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Background: After the initial learning curve associated with mastering a robotic procedure, there is a plateau where operative time and complication rates stabilize. Our objective was to evaluate one surgeon's experience with robotic mitral valve repairs (MVRep) beyond the learning curve and to compare its effectiveness against the traditional open approach.
Methods: Data from Ronald Reagan University of California, Los Angeles Medical Center was prospectively collected from January 2008 to March 2016 to identify adult patients undergoing robotic MVRep. Operative times, complication rates, and cost for robotic versus open MVRep were compared using multivariate regressions, adjusting for comorbidities and previous cardiac surgeries.
Results: During the study period, 175 robotic (41%) and 259 open (59%) MVRep cases were performed at our institution. As the surgeon performed more robotic operations, there was a decrease in room time (554-410 min, P < 0.001), surgery time (405-271 min, P < 0.001), and cross-clamp times (179-93 min, P < 0.001). After application of a multivariate regression model, robotic MVRep was associated with lower odds of complications (odds ratio = 0.42, P = 0.001), shorter length of stay (β = -2.51, P < 0.001), and a reduction of 11% in direct (P = 0.003) and 24% in room costs (P < 0.001), but a 51% increase in surgery cost (P < 0.001).
Conclusions: As the surgeon gained experience with robotic MVRep, operative times decreased in a steady manner. Robotic MVRep had comparable outcomes to open MVRep and lower overall cost. The observed difference in costs is likely related to shorter length of stay and lower room cost with the robotic approach.
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http://dx.doi.org/10.1016/j.jss.2018.10.007 | DOI Listing |
Front Oncol
August 2025
Department of Radiology, The Affiliated Panyu Central Hospital, Guangzhou Medical University, Guangzhou, China.
Objectives: Lymph node metastasis (LNM) is an important factor affecting the stage and prognosis of patients with lung adenocarcinoma. The purpose of this study is to explore the predictive value of the stacking ensemble learning model based on F-FDG PET/CT radiomic features and clinical risk factors for LNM in lung adenocarcinoma, and elucidate the biological basis of predictive features through pathological analysis.
Methods: Ninety patients diagnosed with lung adenocarcinoma who underwent PET/CT were retrospectively analyzed and randomly divided into the training and testing sets in a 7:3 ratio.
Front Oncol
August 2025
Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.
Purpose: Identifying radiomics features that help predict whether glioblastoma patients are prone to developing epilepsy may contribute to an improvement of preventive treatment and a better understanding of the underlying pathophysiology.
Materials And Methods: In this retrospective study, 3-T MRI data of 451 pretreatment glioblastoma patients (mean age: 61.2 ± 11.
J Inflamm Res
September 2025
Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Introduction: While nucleus pulposus cell (NPC) degeneration is a primary driver of intervertebral disc degeneration (IVDD), the cellular heterogeneity and molecular interactions underlying NPC degeneration remain poorly characterized. Previous studies have shown that EGFR signaling plays a significant role in NPC differentiation and collagen matrix production. Consequently, this study aims to identify the critical downstream regulatory molecule of EGFR in the process of NPC degeneration.
View Article and Find Full Text PDFBiochem Biophys Rep
June 2025
Department of Public Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Background: Synaptic dysfunction and synapse loss occur in Alzheimer's disease (AD). The current study aimed to identify synaptic-related genes with diagnostic potential for AD.
Methods: Differentially expressed genes (DEGs) were overlapped with phenotype-associated module selected through weighted gene co-expression network analysis (WGCNA), and synaptic-related genes.
Front Endocrinol (Lausanne)
September 2025
Department of Orthopedics I, Second Affiliated Hospital, Anhui University of Traditional Chinese Medicine, Hefei, Anhui, China.
Background: Emerging evidence indicates that lactase-mediated histone lactylation can activate osteogenic gene expression and promote bone formation. However, the role of lactylation-related genes (LRGs) in osteoporosis (OP) remains unclear. This study aims to clarify the key roles of LRGs and the molecular mechanisms of related biomarkers in OP.
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